Open Circuit IGBT Fault Classification using Phase Current in a CHB Converter
Bibliographic record
Abstract
Recent field failure reports have showed that power cell faults represent the highest contributor to overall CHB converter failure rates. A big portion of these failures are related to power switches, capacitors, gate driver and control circuit boards. Focusing on power switches faults, they normally fail as short circuit or open circuit. Short circuits are dangerous events, however, there is standard method for fast neutralization. On the other hand, open circuit faults are not as fatal as short circuits. Nonetheless, in some situations, the load could not tolerate current imbalance caused by open circuit faults requiring an effective detection and identification method. In general, IGBT open circuit faults are more difficult to detect, and there is no standard method for detection. As a result, there is an industry need for detection, classification, and identification techniques that can perform effectively under different motor loading conditions. In this paper, a proposed method for classifying cell faults caused by IGBT open circuit is presented. Simulation results are provided in order to evaluate the performance of the proposed method.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".